Supplementary Information:
RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods

Aliaksei Z. Holik^1,7, Charity W. Law^2,7, Ruijie Liu²,
Zeya Wang^4,5, Wenyi Wang⁵, Jaeil Ahn⁶, Marie-Liesse Asselin-Labat^1,7, Gordon K. Smyth^3,8 and Matthew E. Ritchie^1,7,8

1. ACRF Stem Cells and Cancer Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
2. Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
3. Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
4. Statistics Department, George R. Brown School of Engineering, Rice University, Houston, Texas, USA
5. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
6. Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University School of Medicine, Washington, DC, USA
7. Department of Medical Biology, The University of Melbourne, Parkville, Australia
8. School of Mathematics and Statistics, The University of Melbourne, Parkville, Australia

Raw Sequence Data

The raw data is available from GEO under accession number GSE86337 (pilot experiment) and GSE64098 (full mixture experiment).

Scripts and Processed Data

Preprocessing and Counting [Read Alignment] [Preprocessing (R scripts and rda files tar gzipped, 141 MB)]

Differential Expression Analysis (main article) [html] [Rmarkdown]
Plots from main article [html] [Rmarkdown]

Differential Expression Analysis (extra analysis, using 0.5 CPM cut-off) [html] [Rmarkdown]
Plots from extra analysis [html] [Rmarkdown]

Differential Splicing Analysis (good samples) [html] [Rmarkdown]

Differential Splicing Analysis (extra analysis, with degraded samples) [html] [Rmarkdown]

Deconvolution Analysis [ISOPure] [DeMix html]

Supplementary Materials [R script]